2013 IEEE 10th International Symposium on Biomedical Imaging最新文献_第6页

Domain prior based superpixel propagation for optic cup localization 基于域先验的超像素传播光学杯定位

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556616

N. Tan, Yanwu Xu, Jiang Liu, Wooi-Boon Goh, C. Cheung, T. Aung, T. Wong

{"title":"Domain prior based superpixel propagation for optic cup localization","authors":"N. Tan, Yanwu Xu, Jiang Liu, Wooi-Boon Goh, C. Cheung, T. Aung, T. Wong","doi":"10.1109/ISBI.2013.6556616","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556616","url":null,"abstract":"In this paper, we present an unsupervised framework using domain priors extracted from the primary structures of the optic nerve head for automated optic cup localization. Our approach provides 3 major contributions. First, we identify a new domain prior, optic cup origin. This prior is derived from the physiological understanding that the central retinal vessels traces its origin from the optic cup before extending to the rest of the retinal. Second, we propose extracting the features of the optic nerve head from superpixels, which are obtained from low-level grouping and have more natural and descriptive features than pixel based techniques. Third, the domain knowledge comprising of optic cup origin and cup pallor, and the extracted features from superpixels are then used to drive a similarity-based label propagation and refinement scheme for the optic cup localization. Our approach was validated on a clinical online dataset, ORIGA-light, of 650 population-based images. Overall, our approach is able to achieve a 32.2% nonoverlap ratio (m1), a 33.8% relative absolute area difference (m2) and a 10.6% absolute CDR error (δ).","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122819045","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Iterative denoising algorithms for perfusion C-arm CT with a rapid scanning protocol 灌注c臂CT快速扫描的迭代去噪算法

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556704

M. Manhart, A. Fieselmann, Y. Deuerling-Zheng, M. Kowarschik

{"title":"Iterative denoising algorithms for perfusion C-arm CT with a rapid scanning protocol","authors":"M. Manhart, A. Fieselmann, Y. Deuerling-Zheng, M. Kowarschik","doi":"10.1109/ISBI.2013.6556704","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556704","url":null,"abstract":"Tissue perfusion measurement using C-arm angiography systems capable of CT-like imaging (C-arm CT) is a novel technique with potentially high benefit for catheter-guided treatment of stroke in the interventional suite. New rapid scanning protocols with increased C-arm rotation speed enable fast acquisitions of C-arm CT volumes and allow for sampling the contrast flow with improved temporal resolution. However, the peak contrast attenuation values of brain tissue lie typically in a range of 5-30 HU. Thus perfusion imaging is very sensitive to noise. In this work we compare different denoising algorithms based on the algebraic reconstruction technique (ART) and introduce a novel denoising technique, which requires only iterative filtering in volume space and is computationally much more attractive. Our evaluation using a realistic digital brain phantom shows that all methods improve the perfusion maps perceptibly compared to Feldkamp-type (FDK) reconstruction. The volume-based technique performs similarly to the ART-based methods: the Pearson correlation of reference and reconstructed blood flow maps increases from 0.61 for the FDK method to 0.81 for the best ART method and to 0.79 for the volume-based method. Furthermore results from a canine stroke model study are shown.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"71 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126268909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Assessing regularity and variability of cortical folding patterns of dicccols 评估双晶状体皮层折叠模式的规律性和可变性

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556639

Jia Chen, Jianfeng Lu, Hanbo Chen, Dajiang Zhu, Tianming Liu

引用次数: 0

X-ray differential phase contrast and dark-field computed tomography and radiography with microbubbles as contrast agent 用微泡作对比剂的x射线差相衬、暗场计算机断层扫描和射线照相

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556757

Xiangyang Tang, Yi Yang

{"title":"X-ray differential phase contrast and dark-field computed tomography and radiography with microbubbles as contrast agent","authors":"Xiangyang Tang, Yi Yang","doi":"10.1109/ISBI.2013.6556757","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556757","url":null,"abstract":"Motivated to improve the low contrast detectability of x-ray imaging in soft tissues, increasing effort has been devoted to the research and development of refraction-based x-ray phase contrast imaging. Among all existing implementations, the x-ray tube and grating based differential phase contrast imaging is of high potential to become an imaging modality for preclinical and eventually clinical applications. Based on our preliminary investigation and recognizing the clinical success of iodine contrast agent in conventional attenuation-based x-ray imaging, we propose the grating-based x-ray differential phase contrast and dark-field imaging method with microbubbles as the contrast agent. Via computer simulation, we investigate the feasibility of the proposed x-ray differential phase contrast and dark-field computed tomography in this work. Preliminary data show that at the detector cell dimension adequate for both clinical (>100μm) and preclinical (≤100μm) applications, the contrast between microbubbles and soft tissues in x-ray differential phase contrast and dark-field computed tomography images is substantially larger than its counterpart in the conventional attenuation-based CT, which encourages further in-depth investigation along this scientific and technological avenue.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116727420","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

PSAR: Predictive space aggregated regression and its application in valvular heart disease classification 预测空间聚合回归及其在瓣膜性心脏病分类中的应用

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556676

Ting Chen, Ritwik K. Kumar, G. Troianowski, T. Syeda-Mahmood, D. Beymer, K. Brannon

{"title":"PSAR: Predictive space aggregated regression and its application in valvular heart disease classification","authors":"Ting Chen, Ritwik K. Kumar, G. Troianowski, T. Syeda-Mahmood, D. Beymer, K. Brannon","doi":"10.1109/ISBI.2013.6556676","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556676","url":null,"abstract":"This paper presents a predictive space aggregated regression based boosting algorithm, and its application in classifying the Continuous Wave(CW) Flow Doppler image data set with the diseases of stenosis and regurgitation in mitral and aortic valves. The proposed algorithm involves finding a way to simultaneously combine all the weak learners based on a well-justified assumption as in the previous work[1] that not only the weak learners but each training sample should have different contributions toward learning the final strong hypothesis. However, the proposed algorithm greatly improves on the previous method by (1) dramatically reducing the number of combination weights, leading to a more stable numerical solution, (2) having regularization in both data and predictive spaces to reduce the generalization error of the model, and (3) using the sparse weight selection scheme in the testing to further avoid overfitting. A sparse subset of the training data is chosen to best approximate the test sample, and the final hypothesis is constructed based only on the chosen training samples and associated weak learner weights. Finally, we empirically show that the proposed technique not only successfully solves the overfitting problem but also significantly increases the performance of the weak classifiers via a set of comparison experiments on the CW Flow Doppler image data set consisting of 4 types of valvular diseases at different severity levels.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121674589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 4

Learning based automatic head detection and measurement from fetal ultrasound images via prior knowledge and imaging parameters 基于先验知识和成像参数的胎儿超声图像自动头部检测和测量

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556589

Dong Ni, Yong Yang, Shengli Li, J. Qin, S. Ouyang, Tianfu Wang, P. Heng

{"title":"Learning based automatic head detection and measurement from fetal ultrasound images via prior knowledge and imaging parameters","authors":"Dong Ni, Yong Yang, Shengli Li, J. Qin, S. Ouyang, Tianfu Wang, P. Heng","doi":"10.1109/ISBI.2013.6556589","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556589","url":null,"abstract":"A novel learning based automatic method is proposed to detect the fetal head for the measurement of head circumference from ultrasound images. We first exploit the AdaBoost learning method to train the classifier on Haar-like features and then, for the first time, we propose to use prior knowledge and online imaging parameters to guide the sliding window based head detection from ultrasound images. This approach can significantly improve both detection rate and speed. The boundary of the head in the localized region is further detected using a local phase based method, which is insensitive to speckle noises and intensity changes in ultrasound images. Finally iterative randomized Hough transform (IRHT) is employed to determine an ellipse on the head contour. Experiments performed on 675 images (500 for classifier training and 175 for measurement) showed that mean-signed difference between automatic and manual measurements is 2.86 mm (1.6%). The statistical analysis further indicated that there was no significant difference between these two measurements. These results demonstrated the proposed fully automatic framework can be used as a consistent and accurate tool in clinical practice.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"9 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116776564","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 21

Real-time anticipation of organ displacement for MR-guidance of interventional procedures 实时预测器官位移用于介入手术的mr指导

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556800

B. D. Senneville, M. Ries, C. Moonen

{"title":"Real-time anticipation of organ displacement for MR-guidance of interventional procedures","authors":"B. D. Senneville, M. Ries, C. Moonen","doi":"10.1109/ISBI.2013.6556800","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556800","url":null,"abstract":"Modern Magnetic Resonance Imaging (MRI) methods now allow the rapid acquisition of images with an excellent tissue contrast and high spatial resolution. Complex organ deformations can thus be estimated using image registration techniques applied to anatomical information. This opens great perspectives for the use of MRI to retroactively target an interventional procedure in mobile organs in real-time. For this purpose, both the update time and the latency of the motion information are two key points. In the current paper, the organ deformation is estimated on a voxel-by-voxel basis and a Kalman predictor is used to compensate for the residual latency. The implementation benefitted from the parallel architecture of Graphical Processing Units (GPU) for accelerating computation times. The efficiency and the potential of the method to anticipate organ displacements in real-time was evaluated on the abdomen of twelve free-breathing volunteers. The deformation of both kidney and liver could be updated with a rate of 10 Hz over sustained periods of several minutes, and the employed Kalman predictor reduced the tracking error in average by 30%.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114047590","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Measuring longitudinally dynamic cortex development in infants by reconstruction of consistent cortical surfaces 通过重建一致的皮质表面来测量婴儿纵向动态皮质发育

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556790

Gang Li, Jingxin Nie, Li Wang, F. Shi, J. Gilmore, Weili Lin, D. Shen

{"title":"Measuring longitudinally dynamic cortex development in infants by reconstruction of consistent cortical surfaces","authors":"Gang Li, Jingxin Nie, Li Wang, F. Shi, J. Gilmore, Weili Lin, D. Shen","doi":"10.1109/ISBI.2013.6556790","DOIUrl":"https://doi.org/10.1109/ISBI.2013.6556790","url":null,"abstract":"Quantitative measurement of dynamic cortex development during early postnatal stages is of great importance to understand early cortical structural and functional development. Conventional methods usually independently reconstruct cortical surfaces of longitudinal images from the same infant, which often generates longitudinallyinconsistent cortical surfaces and leads to inconsistence in cortex development measurement. This paper aims to address this problem by presenting a method to reconstruct consistent cortical surfaces from longitudinal brain MR images in the first-year infants for accurate and consistent measurement of dynamic cortex development. Specifically, longitudinal development of the inner cortical surface is first modeled by a deformable sheet with elasto-plasticity property to establish longitudinally smooth correspondences of inner cortical surfaces. Then, the modeled longitudinal inner cortical surfaces are jointly deformed to locate inner and outer cortical surfaces with a spatial-temporal deformable surface. The method has been applied on 10 infants, each with 5 or 6 scans acquired at every 3 months from birth. Experimental results show that our method can accurately and consistently reconstruct dynamic cortical surfaces from longitudinal infant images, with the average surface distance as low as 0.2mm. By using our method, we can quantitatively characterize longitudinally dynamic cortical thickness development in the first-year infants.","PeriodicalId":178011,"journal":{"name":"2013 IEEE 10th International Symposium on Biomedical Imaging","volume":"45 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125689543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

CRF-driven multi-compartment geometric model crf驱动多隔室几何模型

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556669

Sepehr Farhand, F. Andreopoulos, G. Tsechpenakis

引用次数: 0

Automated posteriorwall thickness measurement from B-mode ultrasound b超自动后壁厚度测量

2013 IEEE 10th International Symposium on Biomedical Imaging Pub Date : 2013-04-07 DOI: 10.1109/ISBI.2013.6556416

Pavan Annangi, N. Subramanian, S. Govind, G. Swamy, B. Young

引用次数: 3